Implementation of Iron Loss Model on Graphic Processing Units

• Published in: IEEE transactions on magnetics Vol. 52; no. 3; pp. 1 - 4
• Main Authors: Hussain, Sajid, Silva, Rodrigo C. P., Lowther, David A.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computation; Computational modeling; Computer simulation; Finite element analysis; Finite element method; Graphic processing unit (GPUs); Graphics processing units; Hardware; Hysteresis; Iron; iron loss; Jiles-Atherton model; Magnetic hysteresis; Magnetism; Mathematical model; parallel processing; Random access memory; Solid modeling; Tasks; Finite-element method (FEM); graphic processing unit (GPU); Jiles–Atherton (JA) model; parallel processing; iron loss
• ISSN: 0018-9464; 1941-0069
• DOI: 10.1109/TMAG.2015.2487959

Design engineers are always looking for extra computational power to speed up the execution of their tasks. One way to achieve this speedup is to identify tasks with a high degree of parallelism and process them with graphic processing units (GPUs). GPUs are optimized to process such tasks efficiently and quickly in massive multicore hardware. The steps involved in a finite-element (FE) electromagnetic simulation are computationally very expensive. One such step is the communication between FE solver and the material loss model that takes place for all the elements in the mesh for each time step. This task is massively parallel and, thus, could be executed in a GPU. As an example, a physics-based material model, the Jiles-Atherton model, is implemented in a GPU to compute the B-H hysteretic relationship, which can be directly incorporated in FE simulations. The performance of the GPU is compared with that of the given microprocessor in terms of computational time. A time gain of 13.8 times has been achieved.